Metatranscriptomics reveals interactions between phototrophs and heterotrophs in freshwater

new plan: table 1: metadata table 2-4: categories by lake - last column getting cutoff? Figure 1: cyclic trends example Figure 2: barplots category by lake

table 2-4 plan: category| % expressed in day (genes/reads) | % expressed in night (genes/reads) | % cyclic

Main text tables and figures.

Table 1. Comparison of Sparkling Lake, Lake Mendota, and Trout Bog. These three lakes were chosen for comparative metatranscriptomics because of their varying trophic statuses, extensive historical data, and previous microbial sampling. Data on surface area, maximum depth, and development on shoreline courtesy of NTL-LTER <lter.limnology.wisc.edu>. Temperature, dissolved oxygen, pH, and conductivity were measured using a HydroLab DS5x Sonde and are averaged over all sampling depths and timepoints for each lake. Chlorophyll and phycocyanin concentrations were measured from the integrated epilimnion samples using a methanol extraction protocol and averaged over all timepoints. Secchi depth was measured at the first timepoint for each lake. Bacterial production was quantified via C14-leucine incorporation and averaged over all timepoints. Due to thunderstorms the night of July 8th, the final 1AM timepoint in Sparkling Lake was collected on July 9th instead.

Lake Mendota Trout Bog Sparkling Lake
Surface area (km^2) 39.600 0.001 0.637
Maximum depth (m) 25.3 7.9 20.o
Trophic status Eutrophic Humic Oligotrophic
Location Madison, WI USA Boulder Junction, WI USA Boulder Junction, WI USA
GPS Coordinates 43.1113, -89.4255 46.0412, -89.6861 46.0091, -89.6695
Shoreline development High Low Moderate
Epilimnion sampling depth 0-7m 0-1.5m 0-4m
Temperature (C) 24.61 19.51 23.33
Dissolved oxygen (mg/L) 9.71 5.33 9.25
pH 8.64 4.03 7.52
Conductivity (uS/cm) 608 25.87 174.54
Total phosphorus (ug/L) 18.81 23.17 6.44
Total nitrogen (ug/L) 625.83 667.98 346.46
Total dissolved phosphorus (ug/L) 8.83 15.41 5.42
Total dissolved nitrogen (ug/L) 506.7 587.51 305.17
Chlorophyll (ug/L) 6.14 14.44 1.77
Phycocyanin (ug/L) 0.74 1.94 3.15
Bacterial production (cpm) 60.02 30.3 3.15
Secchi depth (m) 4.8 1.1 6.2
Sampling dates (2016) July 14-16 July 8-10 July 6-9
Sunrise/sunset time 5:32/20:35 5:18/20:49 5:17/20:50

Table 2. Gene diffs in Lake Mendota

Number of genes % Genes more expressed in day % Genes more expressed at night % Cyclic genes (12 hr phase) p-value from t-test of day vs. night read totals Day/night ratio
Photosynthesis 637 46.47 30.61 21.51 0 2.57
Rhodopsins 124 29.03 22.58 13.71 0.04 1.37
RuBisCO 63 23.81 4.76 0 0.67 1.15
reductive TCA 14 7.14 21.43 0 0.08 1.23
Polyamines 51 0 43.14 0 0.41 0.9
Reactive oxygen species 63 39.68 3.17 15.87 0 1.76
Protease 252 20.63 5.16 7.54 0.02 1.22
Ribose transport 28 0 46.43 0 0.02 0.75
General sugar transport 237 44.3 33.76 5.06 0.02 1.39
Raffinose/stachyose/melibiose transport 25 0 68 0 0 0.58
Glucose/mannose transport 36 0 16.67 0 0.48 0.9
Rhamnose transport 11 0 54.55 0 0.16 0.84
Xylose transport 45 2.22 6.67 0 0.83 0.96
Amino acid transport 258 8.91 12.02 1.94 0.4 1.08

Table 3. Gene diffs in Trout Bog

Number of genes % Genes more expressed in day % Genes more expressed at night % Cyclic genes (12 hr phase) p-value from t-test of day vs. night read totals Day/night/ratios
Photosynthesis 324 52.78 18.52 4.01 0.01 7
RuBisCO 59 32.2 3.39 1.69 0.01 7
Glycoside hydrolases 13 23.08 15.38 0 0.66 0.94
Polyamines 19 5.26 10.53 0 0.05 0.76
Reactive oxygen species 58 29.31 10.34 0 0.21 1.22
Protease 231 18.61 12.12 0 0.05 1.56
Ribose transport 43 0 46.51 0 0 0.42
General sugar transport 63 6.35 49.21 3.17 0 0.55
Xylose transport 15 0 33.33 0 0.02 0.58
Methane/ammonia monooxygenase 24 12.5 33.33 0 0.06 0.67
Amino acid transport 101 2.97 24.75 0 0.02 0.67

Table 3. Gene diffs in Sparkling Lake

Number of genes % Genes more expressed in day % Genes more expressed at night % Cyclic genes (12 hr phase) p-value from t-test of day vs. night read totals Day/night ratio
Photosynthesis 573 30.89 10.47 16.23 0 2.76
Rhodopsins 95 6.32 1.05 2.11 0.77 0.95
RuBisCO 97 0 1.03 0 0.08 0.66
Polyamines 23 4.35 13.04 0 0.18 0.8
Alkaline phosphatase 12 0 0 0 0.13 0.62
Reactive oxygen species 68 29.41 1.47 14.71 0 1.87
Protease 278 10.79 0 2.16 0.14 1.46
Carboxylate transport 27 7.41 0 3.7 0.15 1.26
Ribose transport 13 0 7.69 0 0.07 0.69
General sugar transport 102 6.86 3.92 1.96 0.48 0.88
Raffinose/stachyose/melibiose transport 11 0 0 0 0.02 0.53
Glucose/mannose transport 15 0 0 0 0.14 0.77
Xylose transport 17 0 0 0 0.28 0.76
Fructose transport 13 0 0 0 0.09 0.69
Amino acid transport 158 3.16 0 0.63 0.31 1.18

Figure 1. Cyclic trends in Lake Mendota. Cyclic trends with a 12 hour phase were detected in Lake Mendota for several functional categories.

Supp Figure . Top 10 most expressed annotated heterotrophic genes in each study site. Coding regions from reference genomes and metagenome assemblies were clustered at 97% sequence similarity, and the longest coding region was chosen as the representative sequence. Metatranscriptomic reads were mapped to these representative sequences. The top 10 most expressed genes from each lake, filtered to exclude photosynthetic genes, phototrophic organisms, hypothetical genes, and unclassified genes, are presented here. Annotations and classifications are derived from the sequence to which each read mapped.

Supp Figure. Most highly expressed or abundant phyla by lake. To determine which phyla were most abundant or most expressed during our time series, we analyzed metagenomic and metatranscriptomic read counts. The expression of clustered, nonredundant genes was aggregated by phylum and compared to the coverage of those phyla in metagenomes. Genes that could not be classified in a phylum were not included in this analysis. No positive relationship was observed between expression and abundance. Color indicates the type of phylum represented, with grey indicating Archaea, blue for Bacteria, green for Algae, red for multicellular animals, black for protists, and yellow for viruses. The identity of the most expressed and most abundant phyla varied by lake. One phylum, Chloroflexi, was removed from the plot of Lake Mendota due to orders of magnitude higher expression and abundance. This phylum is likely an outlier.

Supp figure. Assessing the variability of metatranscriptomic read counts. One aim of this metatranscriptomic study was to provide information on the variability in gene expression in freshwater that could be used to guide further metatranscriptomic experiments. We calculated the coefficient of variance (CoV) for each gene both within replicates and across samples (A). CoV was lower within replicates than across replicates, indicating that variation across replicates is not technical. High levels of variability were observed in genes from all three lakes. In panel B, three example eigenvectors of genes are shown, including trends for 1) on one day, off the next, 2) up and down across the time series, and 3) observed in only one timepoint.